International Journal of Advanced Engineering Research and Applications (IJAERA) ISSN: Vol. 1, Issue 6, October Big Data and Hadoop

Size: px
Start display at page:

Download "International Journal of Advanced Engineering Research and Applications (IJAERA) ISSN: 2454-2377 Vol. 1, Issue 6, October 2015. Big Data and Hadoop"

Transcription

1 ISSN: , October 2015 Big Data and Hadoop Simmi Bagga 1 Satinder Kaur 2 1 Assistant Professor, Sant Hira Dass Kanya MahaVidyalaya, Kala Sanghian, Distt Kpt. INDIA 2 Assistant Professor, GNDU, RC, Sathiala, INDIA Abstract: In this era data are continuously acquired for a variety of purposes. Data are generated from large-scale simulations, astronomical observatories, high-throughput experiments, or highresolution sensors. As they all are used lead to new discoveries if scientists have adequate tools to extract knowledge from them. Hadoop is a Software platform that process vast amount of data. It helps to manage Big data. Hadoop can handle all types of data from disparate systems: structured, unstructured, log files, pictures, audio files, communications records, etc. In this paper, we discuss the concept of Big data, its sources and its characteristics. Some additional characteristics of Big data further more we describe the platform Hadoop which provides solution for Big data problem. Keywords: Big Data; Era Data; Hadoop; Large-scale Simulations; Astronomical Observatories I. INTRODUCTION Big Data is data whose scale, diversity, and complexity require new architecture, techniques, algorithms, and analytics to manage it and extract value and hidden knowledge from it. Big data is a voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information. Although big data doesn't refer to any specific quantity the term is often used when speaking about petabytes and exabytes of data etc. But today Big data can describe with 3Vs: the extreme Volume of data, the wide Variety of types of data and the Velocity at which data is traversing. As Big data takes too much time and costs too much money to load into a traditional relational database for analysis. So, new approaches to storing and analyzing data have been emerged which rely less on data schema and data quality. The goal of big data management is to ensure a high level of data quality and accessibility for business intelligence and big data analytics applications. Corporations, government agencies and other organizations employ big data management strategies to help them compete with fast-growing pools of data, typically involving many terabytes or even petabytes of information which have been saved in a variety of file formats. Effective big data management helps companies to locate and represent valuable information in large sets of unstructured data and semi-structured data from a variety of sources, including call detail records, system logs and social media sites. There are huge volumes of data in the world. Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or does not fit the structures of existing database architectures. From the beginning of recorded time until 2003, we created 5 billion gigabytes (exabytes) of data. In 2011, the same amount was created every two days. In 2013, the same amount of data is created in every 10 minutes. 90% of the data in the world today has been created in the last two years alone. There are two major architectural changes that are needed in the traditional integration platforms in order to fulfill future requirements. First, the ability and needs for organizations to store 2015, IJAERA - All Rights Reserved 233

2 and use big data. Most of the big data should always be available for a longtime and there should be tools and techniques available to process be same for the business benefits. Then second, the need for predictive analytical model which must be based on the history or patterns of past or hypothetical data driven models. While the business intelligence deals with what has happened, business analytics deal with what is expected to happen that is to forecast the situation. II. SOURCES OF BIG DATAT Big data comes from different sources like sensors which are used to gather climate information from social media sites while posting digital pictures and videos from transaction records while purchasing goods, and from cell phone GPS signals etc. as shown in fig1. Using social media like Facebook we produce lots of big data when we use to look it as when we look at another person's timeline, send or receive a message, when we post things like photos or videos on Facebook etc. We receive data from or about the computer, mobile phone, or other devices you use to install Facebook apps or to access Facebook.We receive data whenever we visit a game, application, or website that uses Facebook Platform. Sometimes we get data from some advertising partners, customers and other third parties that help us to deliver ads. Fig1. Sources of Big Data Different Physical Sensor data also produces high velocity, volume, variety of data. Sensors are used for geolocation, temperature, noise, attention, engagement, biometrics purposes to collect data in a variety of ways. When we use this large data to user context and to predict behavior we have to process this huge data that is a big challenge , IJAERA - All Rights Reserved 234

3 The progress and innovation is no longer hindered by the ability to collect data. But, by the ability to manage, analyze, summarize, visualize, and discover knowledge from the collected data in a timely manner and in a scalable fashion is necessary. III. CHARACTERISTICS OF BIG DATA "Big Data are high-volume, high-velocity, and/or high-variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization Gartner 2012.Big data can be described by the following characteristics: 3(a). Main Charactristics i.e. 3 V s I. Volume Big data management software enables organizations to store, manage, and manipulate vast amounts of data at the right speed and at the right time. It is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered as Big Data or not. The quantity of data that is generated is very important in this context. Which data is generated by machines, networks and human interaction on systems like social media is very massive. The name Big Data itself contains a term which is related to characterized size that describe it. II. Variety Variety describes different formats of data. These include a long list of data such as documents, s, social media text messages, video, still images, audio, graphs, and the output from all types of machine-generated data from sensors, cell phone GPS signals, DNA analysis devices, and more. This type of data is characterized as unstructured or semi-structured. This variety of unstructured data creates problems for storage, mining and analyzing it. Unstructured data is growing much more rapidly than structured data. It is estimated that unstructured data doubles every three months and offers the example that there are seven million web pages added each day. There are two primary challenges regarding variety of data. First, storing and retrieving these data types quickly and cost efficiently. Second, during analysis, blending or aligning data types from different sources so that all types of data describing a single event can be extracted and analyzed together. III. Velocity Today Data is generated too fast and also need to be processed fast. Big Data Velocity deals with the pace at which data flows in from sources like business processes, machines, networks and human interaction with things like social media sites, mobile devices, etc. The flow of data is massive and continuous. This real-time data can help researchers only if you are able to handle the velocity. Velocity is applied to data in motion. There are various information streams and the increase in sensor network deployment has led to a constant flow of data at a pace that has made it impossible for traditional systems to handle. Initially analysis of data is done by using a batch process. With the new sources of data such as social and mobile applications, the batch process breaks down. The data is now streaming into the server in real time, in a continuous fashion and the result is only useful if the delay is very short , IJAERA - All Rights Reserved 235

4 Figure: 2. How 3 V s exploring 3(b). Additional Characteristics I. Veracity Big Data Veracity refers to the biases, noise and abnormality in data. Is the data that is being stored, and mined meaningful to the problem being analyzed. Veracity in data analysis is the biggest challenge as compared to volume and velocity. In scoping your big data strategy ones need to have his own team and partners together to work to clean the data in the system to avoid dirty data from accumulating in his systems. II. Validity Like big data veracity, the issue of validity deals with the accuracy of data. So that it can be properly use from decision making and fir future conclusions. III. Volatility Big data volatility refers to how long is data valid and how long should it be stored. In this world of real time data one need to determine at what point is data no longer relevant to the current analysis. Big data management clearly deals with issues beyond volume, variety and velocity to other concerns like veracity, validity and volatility to hear about other big data trends and presentation and uses , IJAERA - All Rights Reserved 236

5 IV. HADOOP : A BIG DATA MANAGEMENT PLATFORM Hadoop is a processing engine that is designed to handle extremely high volumes of data in any structure. Hadoop provides distributed storage and distributed processing for very large data sets. Hadoop has two main components: The Hadoop distributed file system (HDFS), which supports data in structured relational form, in unstructured form, and in any form in between. HDFS is a reliable distributed file system that provides high through put access to data. The MapReduce programing paradigm which is meant for managing applications on multiple distributed servers. It is a framework for performing high performance distributed data processing and is based on divide and aggregate paradigm. HDFS, or the Hadoop Distributed File System, gives the programmer unlimited storage. The advantages of HDFS are: Horizontal scalability: Thousands of servers holding petabytes of data. When you need even more storage,we don't switch to more expensive solutions, but add servers instead. Commodity hardware: HDFS is designed with relatively cheap commodity hardware in mind. HDFS is self-healing and replicating. Fault tolerance: Hadoop also deal with hardware failures. If one have 10 thousand servers, then he will see one server fail every day, on average. HDFS foresees that by replicating the data, by default three times, on different data node servers. Thus, if one data node fails, the other two can be used to restore the third one in a different place. MapReduce takes care of distributed computing. It reads the data, usually from its storage, the Hadoop Distributed File System (HDFS), in an optimal way. However, it can read the data from other places too; including mounted local file systems, the web, and databases. It divides the computations between different computers (servers, or nodes). It is also fault-tolerant. If some of nodes fail, Hadoop knows how to continue with the computation, by re-assigning the incomplete work to another node and cleaning up after the node that could not complete its task. It also knows how to combine the results of the computation in one place A set of machines running HDFS and MapReduce is known as a Hadoop Cluster. Individual machines are known as nodes. A cluster can have as few as one node, as many as several thousands. More nodes in the cluster mean better is the performance. These both the components are Hadoop provide ultimate solution to handle the problem of Big data. Hadoop meets all the requirements related to reliability, scalability etc which are the major challenges with the big data. V. CONCLUSION In this paper, we explained big data and its sources. We also explained the characteristics of Big data and also explained how Hadoop can be the solution of the problem of Big Data. Due to the scale, diversity, and complexity of Big data a new architecture, techniques, algorithms, and analytics are required to manage it and extract value and hidden knowledge from it. There are various 2015, IJAERA - All Rights Reserved 237

6 architectural changes that are needed in the traditional platforms in order to overcome future challenges. Hadoop has become a valuable business intelligence tool. Hadoop is a processing engine that is designed to handle extremely high volumes of data in any structure. VI. REFERENCES [1] Beyer, M.A, Laney, D.: The Importance of 'big data': a Definition. Gartner (2012). [2] Kyuseok Shim, MapReduce Algorithms for Big Data Analysis, DNIS [3] VinayakBorkar, Michael J. Carey, Chen Li, Inside Big Data Management :Ogres, Onions, or Parfaits?, EDBT/ICDT 2012 Joint Conference Berlin, Germany,2012 ACM 2012, [4] Hadoop, PoweredbyHadoop, 2015, IJAERA - All Rights Reserved 238

BIG DATA CHALLENGES AND PERSPECTIVES

BIG DATA CHALLENGES AND PERSPECTIVES BIG DATA CHALLENGES AND PERSPECTIVES Meenakshi Sharma 1, Keshav Kishore 2 1 Student of Master of Technology, 2 Head of Department, Department of Computer Science and Engineering, A P Goyal Shimla University,

More information

Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges

Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges Managing Cloud Server with Big Data for Small, Medium Enterprises: Issues and Challenges Prerita Gupta Research Scholar, DAV College, Chandigarh Dr. Harmunish Taneja Department of Computer Science and

More information

Data Refinery with Big Data Aspects

Data Refinery with Big Data Aspects International Journal of Information and Computation Technology. ISSN 0974-2239 Volume 3, Number 7 (2013), pp. 655-662 International Research Publications House http://www. irphouse.com /ijict.htm Data

More information

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK A SURVEY ON BIG DATA ISSUES AMRINDER KAUR Assistant Professor, Department of Computer

More information

Improving Data Processing Speed in Big Data Analytics Using. HDFS Method

Improving Data Processing Speed in Big Data Analytics Using. HDFS Method Improving Data Processing Speed in Big Data Analytics Using HDFS Method M.R.Sundarakumar Assistant Professor, Department Of Computer Science and Engineering, R.V College of Engineering, Bangalore, India

More information

Associate Professor, Department of CSE, Shri Vishnu Engineering College for Women, Andhra Pradesh, India 2

Associate Professor, Department of CSE, Shri Vishnu Engineering College for Women, Andhra Pradesh, India 2 Volume 6, Issue 3, March 2016 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Special Issue

More information

III Big Data Technologies

III Big Data Technologies III Big Data Technologies Today, new technologies make it possible to realize value from Big Data. Big data technologies can replace highly customized, expensive legacy systems with a standard solution

More information

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014

Big Data. White Paper. Big Data Executive Overview WP-BD-10312014-01. Jafar Shunnar & Dan Raver. Page 1 Last Updated 11-10-2014 White Paper Big Data Executive Overview WP-BD-10312014-01 By Jafar Shunnar & Dan Raver Page 1 Last Updated 11-10-2014 Table of Contents Section 01 Big Data Facts Page 3-4 Section 02 What is Big Data? Page

More information

Transforming the Telecoms Business using Big Data and Analytics

Transforming the Telecoms Business using Big Data and Analytics Transforming the Telecoms Business using Big Data and Analytics Event: ICT Forum for HR Professionals Venue: Meikles Hotel, Harare, Zimbabwe Date: 19 th 21 st August 2015 AFRALTI 1 Objectives Describe

More information

Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies

Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies Research Article / Survey Paper / Case Study Available online at: www.ijarcsms.com Image

More information

International Journal of Innovative Research in Computer and Communication Engineering

International Journal of Innovative Research in Computer and Communication Engineering FP Tree Algorithm and Approaches in Big Data T.Rathika 1, J.Senthil Murugan 2 Assistant Professor, Department of CSE, SRM University, Ramapuram Campus, Chennai, Tamil Nadu,India 1 Assistant Professor,

More information

Surfing the Data Tsunami: A New Paradigm for Big Data Processing and Analytics

Surfing the Data Tsunami: A New Paradigm for Big Data Processing and Analytics Surfing the Data Tsunami: A New Paradigm for Big Data Processing and Analytics Dr. Liangxiu Han Future Networks and Distributed Systems Group (FUNDS) School of Computing, Mathematics and Digital Technology,

More information

Analytics in the Cloud. Peter Sirota, GM Elastic MapReduce

Analytics in the Cloud. Peter Sirota, GM Elastic MapReduce Analytics in the Cloud Peter Sirota, GM Elastic MapReduce Data-Driven Decision Making Data is the new raw material for any business on par with capital, people, and labor. What is Big Data? Terabytes of

More information

ISSN:2321-1156 International Journal of Innovative Research in Technology & Science(IJIRTS)

ISSN:2321-1156 International Journal of Innovative Research in Technology & Science(IJIRTS) Nguyễn Thị Thúy Hoài, College of technology _ Danang University Abstract The threading development of IT has been bringing more challenges for administrators to collect, store and analyze massive amounts

More information

BIG DATA What it is and how to use?

BIG DATA What it is and how to use? BIG DATA What it is and how to use? Lauri Ilison, PhD Data Scientist 21.11.2014 Big Data definition? There is no clear definition for BIG DATA BIG DATA is more of a concept than precise term 1 21.11.14

More information

Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan

Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan International Journal of Scientific & Engineering Research, Volume 5, Issue 7, July-2014 1156 Data Mining and Data Pre-processing for Big Data Ashish R. Jagdale, Kavita V. Sonawane, Shamsuddin S. Khan

More information

Chapter 7. Using Hadoop Cluster and MapReduce

Chapter 7. Using Hadoop Cluster and MapReduce Chapter 7 Using Hadoop Cluster and MapReduce Modeling and Prototyping of RMS for QoS Oriented Grid Page 152 7. Using Hadoop Cluster and MapReduce for Big Data Problems The size of the databases used in

More information

Introduction to Hadoop and MapReduce

Introduction to Hadoop and MapReduce Introduction to Hadoop and MapReduce THE CONTRACTOR IS ACTING UNDER A FRAMEWORK CONTRACT CONCLUDED WITH THE COMMISSION Large-scale Computation Traditional solutions for computing large quantities of data

More information

Introduction to Engineering Using Robotics Experiments Lecture 17 Big Data

Introduction to Engineering Using Robotics Experiments Lecture 17 Big Data Introduction to Engineering Using Robotics Experiments Lecture 17 Big Data Yinong Chen 2 Big Data Big Data Technologies Cloud Computing Service and Web-Based Computing Applications Industry Control Systems

More information

White Paper. Version 1.2 May 2015 RAID Incorporated

White Paper. Version 1.2 May 2015 RAID Incorporated White Paper Version 1.2 May 2015 RAID Incorporated Introduction The abundance of Big Data, structured, partially-structured and unstructured massive datasets, which are too large to be processed effectively

More information

Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved

Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved Indian Journal of Science The International Journal for Science ISSN 2319 7730 EISSN 2319 7749 2016 Discovery Publication. All Rights Reserved Perspective Big Data Framework for Healthcare using Hadoop

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics April 10, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

BIG DATA TECHNOLOGY. Hadoop Ecosystem

BIG DATA TECHNOLOGY. Hadoop Ecosystem BIG DATA TECHNOLOGY Hadoop Ecosystem Agenda Background What is Big Data Solution Objective Introduction to Hadoop Hadoop Ecosystem Hybrid EDW Model Predictive Analysis using Hadoop Conclusion What is Big

More information

ANALYTICS BUILT FOR INTERNET OF THINGS

ANALYTICS BUILT FOR INTERNET OF THINGS ANALYTICS BUILT FOR INTERNET OF THINGS Big Data Reporting is Out, Actionable Insights are In In recent years, it has become clear that data in itself has little relevance, it is the analysis of it that

More information

Firebird meets NoSQL (Apache HBase) Case Study

Firebird meets NoSQL (Apache HBase) Case Study Firebird meets NoSQL (Apache HBase) Case Study Firebird Conference 2011 Luxembourg 25.11.2011 26.11.2011 Thomas Steinmaurer DI +43 7236 3343 896 thomas.steinmaurer@scch.at www.scch.at Michael Zwick DI

More information

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract

W H I T E P A P E R. Deriving Intelligence from Large Data Using Hadoop and Applying Analytics. Abstract W H I T E P A P E R Deriving Intelligence from Large Data Using Hadoop and Applying Analytics Abstract This white paper is focused on discussing the challenges facing large scale data processing and the

More information

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014

5 Keys to Unlocking the Big Data Analytics Puzzle. Anurag Tandon Director, Product Marketing March 26, 2014 5 Keys to Unlocking the Big Data Analytics Puzzle Anurag Tandon Director, Product Marketing March 26, 2014 1 A Little About Us A global footprint. A proven innovator. A leader in enterprise analytics for

More information

Journal of Environmental Science, Computer Science and Engineering & Technology

Journal of Environmental Science, Computer Science and Engineering & Technology JECET; March 2015-May 2015; Sec. B; Vol.4.No.2, 202-209. E-ISSN: 2278 179X Journal of Environmental Science, Computer Science and Engineering & Technology An International Peer Review E-3 Journal of Sciences

More information

Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics

Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics Finding Insights & Hadoop Cluster Performance Analysis over Census Dataset Using Big-Data Analytics Dharmendra Agawane 1, Rohit Pawar 2, Pavankumar Purohit 3, Gangadhar Agre 4 Guide: Prof. P B Jawade 2

More information

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database

Managing Big Data with Hadoop & Vertica. A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Managing Big Data with Hadoop & Vertica A look at integration between the Cloudera distribution for Hadoop and the Vertica Analytic Database Copyright Vertica Systems, Inc. October 2009 Cloudera and Vertica

More information

The Rise of Industrial Big Data

The Rise of Industrial Big Data GE Intelligent Platforms The Rise of Industrial Big Data Leveraging large time-series data sets to drive innovation, competitiveness and growth capitalizing on the big data opportunity The Rise of Industrial

More information

Efficient Analysis of Big Data Using Map Reduce Framework

Efficient Analysis of Big Data Using Map Reduce Framework Efficient Analysis of Big Data Using Map Reduce Framework Dr. Siddaraju 1, Sowmya C L 2, Rashmi K 3, Rahul M 4 1 Professor & Head of Department of Computer Science & Engineering, 2,3,4 Assistant Professor,

More information

Big Data: Tools and Technologies in Big Data

Big Data: Tools and Technologies in Big Data Big Data: Tools and Technologies in Big Data Jaskaran Singh Student Lovely Professional University, Punjab Varun Singla Assistant Professor Lovely Professional University, Punjab ABSTRACT Big data can

More information

Hadoop IST 734 SS CHUNG

Hadoop IST 734 SS CHUNG Hadoop IST 734 SS CHUNG Introduction What is Big Data?? Bulk Amount Unstructured Lots of Applications which need to handle huge amount of data (in terms of 500+ TB per day) If a regular machine need to

More information

Are You Ready for Big Data?

Are You Ready for Big Data? Are You Ready for Big Data? Jim Gallo National Director, Business Analytics February 11, 2013 Agenda What is Big Data? How do you leverage Big Data in your company? How do you prepare for a Big Data initiative?

More information

BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON

BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON BIG DATA IN THE CLOUD : CHALLENGES AND OPPORTUNITIES MARY- JANE SULE & PROF. MAOZHEN LI BRUNEL UNIVERSITY, LONDON Overview * Introduction * Multiple faces of Big Data * Challenges of Big Data * Cloud Computing

More information

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D.

Big Data Technology ดร.ช ชาต หฤไชยะศ กด. Choochart Haruechaiyasak, Ph.D. Big Data Technology ดร.ช ชาต หฤไชยะศ กด Choochart Haruechaiyasak, Ph.D. Speech and Audio Technology Laboratory (SPT) National Electronics and Computer Technology Center (NECTEC) National Science and Technology

More information

A STUDY ON HADOOP ARCHITECTURE FOR BIG DATA ANALYTICS

A STUDY ON HADOOP ARCHITECTURE FOR BIG DATA ANALYTICS A STUDY ON HADOOP ARCHITECTURE FOR BIG DATA ANALYTICS Dr. Ananthi Sheshasayee 1, J V N Lakshmi 2 1 Head Department of Computer Science & Research, Quaid-E-Millath Govt College for Women, Chennai, (India)

More information

Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum

Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum Trends and Research Opportunities in Spatial Big Data Analytics and Cloud Computing NCSU GeoSpatial Forum Siva Ravada Senior Director of Development Oracle Spatial and MapViewer 2 Evolving Technology Platforms

More information

Danny Wang, Ph.D. Vice President of Business Strategy and Risk Management Republic Bank

Danny Wang, Ph.D. Vice President of Business Strategy and Risk Management Republic Bank Danny Wang, Ph.D. Vice President of Business Strategy and Risk Management Republic Bank Agenda» Overview» What is Big Data?» Accelerates advances in computer & technologies» Revolutionizes data measurement»

More information

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM

A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM A REVIEW PAPER ON THE HADOOP DISTRIBUTED FILE SYSTEM Sneha D.Borkar 1, Prof.Chaitali S.Surtakar 2 Student of B.E., Information Technology, J.D.I.E.T, sborkar95@gmail.com Assistant Professor, Information

More information

Large scale processing using Hadoop. Ján Vaňo

Large scale processing using Hadoop. Ján Vaňo Large scale processing using Hadoop Ján Vaňo What is Hadoop? Software platform that lets one easily write and run applications that process vast amounts of data Includes: MapReduce offline computing engine

More information

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing

Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Architecting for Big Data Analytics and Beyond: A New Framework for Business Intelligence and Data Warehousing Wayne W. Eckerson Director of Research, TechTarget Founder, BI Leadership Forum Business Analytics

More information

Big Data Components for Business Process Optimization

Big Data Components for Business Process Optimization 72 Big Data Components for Business Process Optimization Mircea Răducu TRIFU, Mihaela-Laura IVAN Bucharest University of Economic Studies, Bucharest, Romania trifumircearadu@yahoo.com, ivanmihaela88@gmail.com

More information

locuz.com Big Data Services

locuz.com Big Data Services locuz.com Big Data Services Big Data At Locuz, we help the enterprise move from being a data-limited to a data-driven one, thereby enabling smarter, faster decisions that result in better business outcome.

More information

BIG DATA & ANALYTICS. Transforming the business and driving revenue through big data and analytics

BIG DATA & ANALYTICS. Transforming the business and driving revenue through big data and analytics BIG DATA & ANALYTICS Transforming the business and driving revenue through big data and analytics Collection, storage and extraction of business value from data generated from a variety of sources are

More information

Suresh Lakavath csir urdip Pune, India lsureshit@gmail.com.

Suresh Lakavath csir urdip Pune, India lsureshit@gmail.com. A Big Data Hadoop Architecture for Online Analysis. Suresh Lakavath csir urdip Pune, India lsureshit@gmail.com. Ramlal Naik L Acme Tele Power LTD Haryana, India ramlalnaik@gmail.com. Abstract Big Data

More information

Big Data with Rough Set Using Map- Reduce

Big Data with Rough Set Using Map- Reduce Big Data with Rough Set Using Map- Reduce Mr.G.Lenin 1, Mr. A. Raj Ganesh 2, Mr. S. Vanarasan 3 Assistant Professor, Department of CSE, Podhigai College of Engineering & Technology, Tirupattur, Tamilnadu,

More information

IoT and Big Data- The Current and Future Technologies: A Review

IoT and Big Data- The Current and Future Technologies: A Review Available Online at www.ijcsmc.com International Journal of Computer Science and Mobile Computing A Monthly Journal of Computer Science and Information Technology IJCSMC, Vol. 5, Issue. 1, January 2016,

More information

The 3 questions to ask yourself about BIG DATA

The 3 questions to ask yourself about BIG DATA The 3 questions to ask yourself about BIG DATA Do you have a big data problem? Companies looking to tackle big data problems are embarking on a journey that is full of hype, buzz, confusion, and misinformation.

More information

Big Data. Fast Forward. Putting data to productive use

Big Data. Fast Forward. Putting data to productive use Big Data Putting data to productive use Fast Forward What is big data, and why should you care? Get familiar with big data terminology, technologies, and techniques. Getting started with big data to realize

More information

BIG DATA: STORAGE, ANALYSIS AND IMPACT GEDIMINAS ŽYLIUS

BIG DATA: STORAGE, ANALYSIS AND IMPACT GEDIMINAS ŽYLIUS BIG DATA: STORAGE, ANALYSIS AND IMPACT GEDIMINAS ŽYLIUS WHAT IS BIG DATA? describes any voluminous amount of structured, semi-structured and unstructured data that has the potential to be mined for information

More information

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services

Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012. Viswa Sharma Solutions Architect Tata Consultancy Services Hadoop Beyond Hype: Complex Adaptive Systems Conference Nov 16, 2012 Viswa Sharma Solutions Architect Tata Consultancy Services 1 Agenda What is Hadoop Why Hadoop? The Net Generation is here Sizing the

More information

Big Data: Study in Structured and Unstructured Data

Big Data: Study in Structured and Unstructured Data Big Data: Study in Structured and Unstructured Data Motashim Rasool 1, Wasim Khan 2 mail2motashim@gmail.com, khanwasim051@gmail.com Abstract With the overlay of digital world, Information is available

More information

Boarding to Big data

Boarding to Big data Database Systems Journal vol. VI, no. 4/2015 11 Boarding to Big data Oana Claudia BRATOSIN University of Economic Studies, Bucharest, Romania oc.bratosin@gmail.com Today Big data is an emerging topic,

More information

Spatio-Temporal Networks:

Spatio-Temporal Networks: Spatio-Temporal Networks: Analyzing Change Across Time and Place WHITE PAPER By: Jeremy Peters, Principal Consultant, Digital Commerce Professional Services, Pitney Bowes ABSTRACT ORGANIZATIONS ARE GENERATING

More information

Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome

Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome Enhance Collaboration and Data Sharing for Faster Decisions and Improved Mission Outcome Richard Breakiron Senior Director, Cyber Solutions Rbreakiron@vion.com Office: 571-353-6127 / Cell: 803-443-8002

More information

Massive Cloud Auditing using Data Mining on Hadoop

Massive Cloud Auditing using Data Mining on Hadoop Massive Cloud Auditing using Data Mining on Hadoop Prof. Sachin Shetty CyberBAT Team, AFRL/RIGD AFRL VFRP Tennessee State University Outline Massive Cloud Auditing Traffic Characterization Distributed

More information

Hadoop. http://hadoop.apache.org/ Sunday, November 25, 12

Hadoop. http://hadoop.apache.org/ Sunday, November 25, 12 Hadoop http://hadoop.apache.org/ What Is Apache Hadoop? The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using

More information

BIG DATA: BIG CHALLENGE FOR SOFTWARE TESTERS

BIG DATA: BIG CHALLENGE FOR SOFTWARE TESTERS BIG DATA: BIG CHALLENGE FOR SOFTWARE TESTERS Megha Joshi Assistant Professor, ASM s Institute of Computer Studies, Pune, India Abstract: Industry is struggling to handle voluminous, complex, unstructured

More information

Big Data Analytics. Lucas Rego Drumond

Big Data Analytics. Lucas Rego Drumond Big Data Analytics Lucas Rego Drumond Information Systems and Machine Learning Lab (ISMLL) Institute of Computer Science University of Hildesheim, Germany Big Data Analytics Big Data Analytics 1 / 36 Outline

More information

Testing 3Vs (Volume, Variety and Velocity) of Big Data

Testing 3Vs (Volume, Variety and Velocity) of Big Data Testing 3Vs (Volume, Variety and Velocity) of Big Data 1 A lot happens in the Digital World in 60 seconds 2 What is Big Data Big Data refers to data sets whose size is beyond the ability of commonly used

More information

Client Overview. Engagement Situation. Key Requirements

Client Overview. Engagement Situation. Key Requirements Client Overview Our client is one of the leading providers of business intelligence systems for customers especially in BFSI space that needs intensive data analysis of huge amounts of data for their decision

More information

Statistical Challenges with Big Data in Management Science

Statistical Challenges with Big Data in Management Science Statistical Challenges with Big Data in Management Science Arnab Kumar Laha Indian Institute of Management Ahmedabad Analytics vs Reporting Competitive Advantage Reporting Prescriptive Analytics (Decision

More information

Exploring Big Data in Social Networks

Exploring Big Data in Social Networks Exploring Big Data in Social Networks virgilio@dcc.ufmg.br (meira@dcc.ufmg.br) INWEB National Science and Technology Institute for Web Federal University of Minas Gerais - UFMG May 2013 Some thoughts about

More information

BIG DATA FUNDAMENTALS

BIG DATA FUNDAMENTALS BIG DATA FUNDAMENTALS Timeframe Minimum of 30 hours Use the concepts of volume, velocity, variety, veracity and value to define big data Learning outcomes Critically evaluate the need for big data management

More information

Keywords Big Data, NoSQL, Relational Databases, Decision Making using Big Data, Hadoop

Keywords Big Data, NoSQL, Relational Databases, Decision Making using Big Data, Hadoop Volume 4, Issue 1, January 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Transitioning

More information

Why Big Data? Why Now?

Why Big Data? Why Now? Ellis Holman Why Big Data? Why Now? Information is at the Center of a New Wave of Opportunity 44x as much Data and Content Over Coming Decade 2020 35 zettabytes And Organizations Need Deeper Insights 1in3

More information

The Next Wave of Data Management. Is Big Data The New Normal?

The Next Wave of Data Management. Is Big Data The New Normal? The Next Wave of Data Management Is Big Data The New Normal? Table of Contents Introduction 3 Separating Reality and Hype 3 Why Are Firms Making IT Investments In Big Data? 4 Trends In Data Management

More information

Big Data & Analytics. Counterparty Credit Risk Management. Big Data in Risk Analytics

Big Data & Analytics. Counterparty Credit Risk Management. Big Data in Risk Analytics Deniz Kural, Senior Risk Expert BeLux Patrick Billens, Big Data Solutions Leader Big Data & Analytics Counterparty Credit Risk Management Challenges for the Counterparty Credit Risk Manager Regulatory

More information

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY

INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK A REVIEW ON BIG DATA MANAGEMENT AND ITS SECURITY PRUTHVIKA S. KADU 1, DR. H. R.

More information

Of all the data in recorded human history, 90 percent has been created in the last two years. - Mark van Rijmenam, Think Bigger, 2014

Of all the data in recorded human history, 90 percent has been created in the last two years. - Mark van Rijmenam, Think Bigger, 2014 What is Big Data? Of all the data in recorded human history, 90 percent has been created in the last two years. - Mark van Rijmenam, Think Bigger, 2014 Data in the Twentieth Century and before In 1663,

More information

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance.

Keywords Big Data; OODBMS; RDBMS; hadoop; EDM; learning analytics, data abundance. Volume 4, Issue 11, November 2014 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Analytics

More information

Understanding traffic flow

Understanding traffic flow White Paper A Real-time Data Hub For Smarter City Applications Intelligent Transportation Innovation for Real-time Traffic Flow Analytics with Dynamic Congestion Management 2 Understanding traffic flow

More information

Open source Google-style large scale data analysis with Hadoop

Open source Google-style large scale data analysis with Hadoop Open source Google-style large scale data analysis with Hadoop Ioannis Konstantinou Email: ikons@cslab.ece.ntua.gr Web: http://www.cslab.ntua.gr/~ikons Computing Systems Laboratory School of Electrical

More information

BIG DATA TRENDS AND TECHNOLOGIES

BIG DATA TRENDS AND TECHNOLOGIES BIG DATA TRENDS AND TECHNOLOGIES THE WORLD OF DATA IS CHANGING Cloud WHAT IS BIG DATA? Big data are datasets that grow so large that they become awkward to work with using onhand database management tools.

More information

ISSN: 2321-7782 (Online) Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies

ISSN: 2321-7782 (Online) Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies ISSN: 2321-7782 (Online) Volume 3, Issue 6, June 2015 International Journal of Advance Research in Computer Science and Management Studies Research Article / Survey Paper / Case Study Available online

More information

Whitepaper. The Emerging Big Data System - Testing Perspective. : Digital Assurance Practice : Nagarajan K R :

Whitepaper. The Emerging Big Data System - Testing Perspective. : Digital Assurance Practice : Nagarajan K R : Whitepaper The Emerging Big Data System Presented by Author Email Id : Digital Assurance Practice : Nagarajan K R : nagarajankr@hexaware.com Hexaware Technologies. All rights reserved. Table of Contents

More information

Keywords: Big Data, HDFS, Map Reduce, Hadoop

Keywords: Big Data, HDFS, Map Reduce, Hadoop Volume 5, Issue 7, July 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com Configuration Tuning

More information

What happens when Big Data and Master Data come together?

What happens when Big Data and Master Data come together? What happens when Big Data and Master Data come together? Jeremy Pritchard Master Data Management fgdd 1 What is Master Data? Master data is data that is shared by multiple computer systems. The Information

More information

The Challenge of Handling Large Data Sets within your Measurement System

The Challenge of Handling Large Data Sets within your Measurement System The Challenge of Handling Large Data Sets within your Measurement System The Often Overlooked Big Data Aaron Edgcumbe Marketing Engineer Northern Europe, Automated Test National Instruments Introduction

More information

Big Data, Why All the Buzz? (Abridged) Anita Luthra, February 20, 2014

Big Data, Why All the Buzz? (Abridged) Anita Luthra, February 20, 2014 Big Data, Why All the Buzz? (Abridged) Anita Luthra, February 20, 2014 Defining Big Not Just Massive Data Big data refers to data sets whose size is beyond the ability of typical database software tools

More information

NextGen Infrastructure for Big DATA Analytics.

NextGen Infrastructure for Big DATA Analytics. NextGen Infrastructure for Big DATA Analytics. So What is Big Data? Data that exceeds the processing capacity of conven4onal database systems. The data is too big, moves too fast, or doesn t fit the structures

More information

DATA MINING AND WAREHOUSING CONCEPTS

DATA MINING AND WAREHOUSING CONCEPTS CHAPTER 1 DATA MINING AND WAREHOUSING CONCEPTS 1.1 INTRODUCTION The past couple of decades have seen a dramatic increase in the amount of information or data being stored in electronic format. This accumulation

More information

Department of Computer Science Himachal Pradesh University, Shimla, India

Department of Computer Science Himachal Pradesh University, Shimla, India Volume 5, Issue 6, June 2015 ISSN: 2277 128X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com A Study of Hadoop:

More information

The 4 Pillars of Technosoft s Big Data Practice

The 4 Pillars of Technosoft s Big Data Practice beyond possible Big Use End-user applications Big Analytics Visualisation tools Big Analytical tools Big management systems The 4 Pillars of Technosoft s Big Practice Overview Businesses have long managed

More information

Big Data on Microsoft Platform

Big Data on Microsoft Platform Big Data on Microsoft Platform Prepared by GJ Srinivas Corporate TEG - Microsoft Page 1 Contents 1. What is Big Data?...3 2. Characteristics of Big Data...3 3. Enter Hadoop...3 4. Microsoft Big Data Solutions...4

More information

Journal of Chemical and Pharmaceutical Research, 2015, 7(3):1388-1392. Research Article. E-commerce recommendation system on cloud computing

Journal of Chemical and Pharmaceutical Research, 2015, 7(3):1388-1392. Research Article. E-commerce recommendation system on cloud computing Available online www.jocpr.com Journal of Chemical and Pharmaceutical Research, 2015, 7(3):1388-1392 Research Article ISSN : 0975-7384 CODEN(USA) : JCPRC5 E-commerce recommendation system on cloud computing

More information

How to use Big Data in Industry 4.0 implementations. LAURI ILISON, PhD Head of Big Data and Machine Learning

How to use Big Data in Industry 4.0 implementations. LAURI ILISON, PhD Head of Big Data and Machine Learning How to use Big Data in Industry 4.0 implementations LAURI ILISON, PhD Head of Big Data and Machine Learning Big Data definition? Big Data is about structured vs unstructured data Big Data is about Volume

More information

Using Tableau Software with Hortonworks Data Platform

Using Tableau Software with Hortonworks Data Platform Using Tableau Software with Hortonworks Data Platform September 2013 2013 Hortonworks Inc. http:// Modern businesses need to manage vast amounts of data, and in many cases they have accumulated this data

More information

Hadoop implementation of MapReduce computational model. Ján Vaňo

Hadoop implementation of MapReduce computational model. Ján Vaňo Hadoop implementation of MapReduce computational model Ján Vaňo What is MapReduce? A computational model published in a paper by Google in 2004 Based on distributed computation Complements Google s distributed

More information

HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica

HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica HP Vertica at MIT Sloan Sports Analytics Conference March 1, 2013 Will Cairns, Senior Data Scientist, HP Vertica So What s the market s definition of Big Data? Datasets whose volume, velocity, variety

More information

Big Data in Healthcare. Dr. Refael Barkan, M.D. Ph.D. Head of RDE at HIT Bar-Ilan University, May 2016

Big Data in Healthcare. Dr. Refael Barkan, M.D. Ph.D. Head of RDE at HIT Bar-Ilan University, May 2016 Big Data in Healthcare Dr. Refael Barkan, M.D. Ph.D. Head of RDE at HIT Bar-Ilan University, May 2016 What is Big Data? Quite nebulous, in the same way that the term cloud covers diverse technologies To

More information

Big Data Analytics OverOnline Transactional Data Set

Big Data Analytics OverOnline Transactional Data Set Big Data Analytics OverOnline Transactional Data Set Rohit Vaswani 1, Rahul Vaswani 2, Manish Shahani 3, Lifna Jos(Mentor) 4 1 B.E. Computer Engg. VES Institute of Technology, Mumbai -400074, Maharashtra,

More information

What is a Petabyte? Gain Big or Lose Big; Measuring the Operational Risks of Big Data. Agenda

What is a Petabyte? Gain Big or Lose Big; Measuring the Operational Risks of Big Data. Agenda April - April - Gain Big or Lose Big; Measuring the Operational Risks of Big Data YouTube video here http://www.youtube.com/watch?v=o7uzbcwstu April, 0 Steve Woolley, Sr. Manager Business Continuity Dennis

More information

Log Mining Based on Hadoop s Map and Reduce Technique

Log Mining Based on Hadoop s Map and Reduce Technique Log Mining Based on Hadoop s Map and Reduce Technique ABSTRACT: Anuja Pandit Department of Computer Science, anujapandit25@gmail.com Amruta Deshpande Department of Computer Science, amrutadeshpande1991@gmail.com

More information

Manifest for Big Data Pig, Hive & Jaql

Manifest for Big Data Pig, Hive & Jaql Manifest for Big Data Pig, Hive & Jaql Ajay Chotrani, Priyanka Punjabi, Prachi Ratnani, Rupali Hande Final Year Student, Dept. of Computer Engineering, V.E.S.I.T, Mumbai, India Faculty, Computer Engineering,

More information

SQLSaturday #399 Sacramento 25 July, 2015. Big Data Analytics with Excel

SQLSaturday #399 Sacramento 25 July, 2015. Big Data Analytics with Excel SQLSaturday #399 Sacramento 25 July, 2015 Big Data Analytics with Excel Presenter Introduction Peter Myers Independent BI Expert Bitwise Solutions BBus, SQL Server MCSE, SQL Server MVP since 2007 Experienced

More information

A Study on Big-Data Approach to Data Analytics

A Study on Big-Data Approach to Data Analytics A Study on Big-Data Approach to Data Analytics Ishwinder Kaur Sandhu #1, Richa Chabbra 2 1 M.Tech Student, Department of Computer Science and Technology, NCU University, Gurgaon, Haryana, India 2 Assistant

More information